HCL Technologies

Overview of job

You will be responsible for building and running the data processing pipeline on Google Cloud platform

• Work with implementation teams from concept to operations, providing deep technical expertise for successfully deploying large scale data solutions in the enterprise, using modern data/analytics technologies on GCP
• Work with data team to efficiently use GCP to analyze data, build data models, and generate reports/visualizations
• Integrate massive datasets from multiple data sources for data modelling
• Implement methods for Devops automation of all parts of the build data pipelines to deploy from development to production
• Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product management
• Design pipelines and architectures for data processing
• Extract, load, transform, clean and validate data

• Salary up to 4000$ and Joining Bonus up to 30m
• Attractive package including base salary + 13th month salary + Performance Bonus
• Insurance based on full base salary
• Meal allowance 730,000/month
• 100% of full salary and benefits as an official employee from the 1st day of working
• Medical Benefit (Bao Viet Insurance Package) for Employee and Family
• Working in a fast paced, flexible, and multinational working environment with opportunity to travel
  onsite (in 49 countries)
• Internal Training (Technical & Functional & English)
• Working time: 8:30 am - 6:00 pm from Mondays to Fridays

Must requirements:

• At least 2 years of experience in ETL Tools (such as Infromatica, Apache Beam, Kafka)
• At least 1 years of experience in Google Cloud Platform (BigQuery, DataProc, DataFlow)
• Having relative experience in any scripting/programming language as following: Java/Python/Go
• Having relative experience in declarative CI/CD (Jenkins, Azure DevOps)
• Having relative experience in Databases: SQL and NoSQL
• Have a strong engineering mindset to automate tasks, identify use cases, test cases, improve the system, PR/Incident resolution and deployments

Good to Have:

• Having relative experience in Automation: Kubernetes or Docker & Containerization
• Having relative experience in Infrastructure as a Code (IaaC) (i.e., Terraform, Cloud Formation, Azure ARM Templates)
• Having knowledge or experience in Big Data - Hadoop ecosystems including HDFS, MapReduce, YARN, HBase, Zookeeper, Spark, Pig, Hive...
• Having knowledge or experience with Hadoop distributions such as Cloudera, HortonWorks...
• Having relative experience in Data management:
  • Data Governance
  • Data Architecture
  • Data Modelling
  • Data Quality
  • Data integration